Show HN: SkillFortify, Formal verification for AI agents (auto-discovers)
2 points
1 hour ago
| 1 comment
| github.com
| HN
Hi HN,

I posted SkillFortify here a few days ago as a formal verification tool for 3 agent skill formats. Based on feedback, v0.3 now supports 22 agent frameworks and can scan your entire system with zero configuration.

The problem: In January 2026, the ClawHavoc campaign planted 1,200 malicious skills into agent marketplaces. CVE-2026-25253 was the first RCE in agent software. Researchers catalogued 6,000+ malicious agent tools. The industry responded with heuristic scanners — pattern matching, YARA rules, LLM-as-judge. One popular scanner states in its docs: "No findings does not mean no risk."

SkillFortify eliminates that caveat with formal verification.

What it does:

  pip install skillfortify
  skillfortify scan
That's it. No arguments, no config files, no paths. It auto-discovers every AI tool on your machine across 23+ IDE profiles:

  [*] Auto-discovering AI tools on system...
  [+] Found: Claude Code (12 skills)
  [+] Found: Cursor (8 skills)
  [+] Found: VS Code MCP (5 servers)
  [+] Found: Windsurf (3 skills)
  [*] Scanning 28 skills across 4 tools...

  RESULTS
    Critical:  2 skills with capability violations
    High:      3 skills with excessive permissions
    Clean:     23 skills passed all checks
22 supported frameworks: Claude Code, Cursor, VS Code, Windsurf, Gemini, OpenCode, Cline, Continue, Copilot, n8n, Roo, Trae, Kiro, Kode, Jules, Junie, Codex, SuperVS, Zencoder, CommandCode, Factory, Qoder — plus auto-discovery of unknown tools.

Why formal verification, not heuristics: Heuristic scanners check for known bad patterns. Novel attacks pass through. SkillFortify verifies what a skill CAN do against what it CLAIMS to do. Five mathematical theorems guarantee soundness — if it says safe, it provably cannot exceed declared capabilities.

Results on 540-skill benchmark (270 malicious, 270 benign): - F1 = 96.95% - Precision = 100% (zero false positives) - Recall = 94.07% - Speed: ~2.5ms per skill

9 CLI commands: - scan — auto-discover + analyze all AI tools on your system - verify — formally verify a single skill - lock — generate skill-lock.json (like package-lock.json for agent skills) - trust — compute graduated trust score (L0-L3, inspired by SLSA) - sbom — generate CycloneDX 1.6 Agent Software Bill of Materials - frameworks — list all 22 supported frameworks + detection status - dashboard — generate standalone HTML security report (zero dependencies) - registry-scan — scan MCP/PyPI/npm registries before installing - verify --recursive — batch verify entire directory trees

1,818 tests. 22 parsers. 97 source modules. MIT licensed. Peer-reviewed paper on Zenodo.

GitHub: https://github.com/varun369/skillfortify PyPI: https://pypi.org/project/skillfortify/ Paper: https://zenodo.org/records/18787663 Wiki: https://github.com/varun369/skillfortify/wiki Landing page: https://www.superlocalmemory.com/skillfortify

Built this as part of my research on making AI agents reliable enough for production. The companion project AgentAssert (arXiv:2602.22302) handles behavioral contracts — SkillFortify handles the supply chain.

Happy to answer questions about the formal model, framework support, or auto-discovery.

varunpratap369
1 hour ago
[-]
For anyone who wants to try it right now:

    pip install skillfortify
    skillfortify scan
If you have Claude Code, Cursor, VS Code with MCP, or any other AI coding tool installed, it will find them automatically.

To see the HTML dashboard:

    skillfortify dashboard ~/my-project
Opens a standalone HTML file with interactive filters, risk distribution, and per-skill capability breakdowns. Share it with your security team as a single file — they don't need to install anything.

If you find a framework we don't support yet, open an issue. Adding a new parser takes about a day.

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